Evaluation of pre-shot peening on improvement of carburizing heat treatment of AISI 9310 gear steel

Effective hardening depth (EHD) and surface hardness (SH) achieved by carburizing heat treatment play vital roles in guaranteeing the fatigue performance of heavy load carburized gears, which are often subjected to fatigue failure in the engineering practice. In this study, a strategy of combining the pre-shot peening process and subsequent carburizing heat treatment was proposed to improve the efficiency of carburizing heat treatment of AISI 9310 gear steel. Characterizations of hardness, material microstructure, surface roughness and micro-strain of treated roller samples were conducted with helps of a microhardness tester, optical microscopy, scanning electron microscope, white light interferometer and Xray diffraction, respectively. The underlying mechanism was explored in terms of discovering the relationship between EHD and microstructure, plastic deformation, surface roughness. Results indicated that the efficiency of carburization heat treatment of AISI 9310 gear steel has been greatly enhanced by the proposed strategy, leading to an increasing in EHD and an increase of about 36.4 HV in SH, respectively. Additionally, the importance of shot peening intensity and coverage to EHD was analyzed by the random forest (RF) algorithm.(c) 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Automated summary

In this study, a strategy of combining pre-shot peening process and subsequent carburizing heat treatment was proposed to improve the efficiency of carburizing heat treatment of AISI 9310 gear steel. The relationship between effective hardening depth (EHD) and microstructure, plastic deformation, and surface roughness was explored. The results showed that the proposed strategy greatly enhanced the efficiency of carburization heat treatment with an increase in EHD and surface hardness (SH). The importance of shot peening intensity and coverage to EHD was also analyzed using the random forest (RF) algorithm.